Trinity Large Preview vs Llama 3.3 Nemotron Super 49B V1.5
Trinity Large Preview
Llama 3.3 Nemotron Super 49B V1.5
| Trinity Large Preview | Llama 3.3 Nemotron Super 49B V1.5 | |
|---|---|---|
| Provider | Arcee AI | NVIDIA |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary β | 131,000 | 131,072 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | tools, json_mode | tools, json_mode |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary β | 0.1500 | 0.1000 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3β5Γ pricier than input. Glossary β | 0.4500 | 0.4000 |
Frequently asked questions
Which is cheaper, Trinity Large Preview or Llama 3.3 Nemotron Super 49B V1.5?
Llama 3.3 Nemotron Super 49B V1.5 is cheaper than Trinity Large Preview on a 50/50 input/output blend by about $0.05 per 1M tokens. Exact savings depend on your input-vs-output ratio β use the cost calculator on this page for a workload-specific estimate.
Which has a larger context window, Trinity Large Preview or Llama 3.3 Nemotron Super 49B V1.5?
Llama 3.3 Nemotron Super 49B V1.5 has the larger context window at 131k tokens versus 131k tokens for Trinity Large Preview. That means Llama 3.3 Nemotron Super 49B V1.5 can ingest about 1.0x as much text per request.
What is the difference between Trinity Large Preview and Llama 3.3 Nemotron Super 49B V1.5?
Trinity Large Preview comes from Arcee AI; Llama 3.3 Nemotron Super 49B V1.5 comes from NVIDIA. They differ in pricing, context window, and supported capabilities β see the side-by-side table on this page for the exact figures, refreshed nightly.